High throughput calculations for a dataset of bilayer materials
Ranjan Kumar Barik1, Lilia M Woods2
1Department of Physics, University of South Florida, Tampa, Florida, 33620, USA. sran9125@gmail.com.
Scientific Data
|April 21, 2023
Summary
This study presents a computational dataset of 760 bilayer materials, detailing their properties for optoelectronics and thermoelectrics. The findings enable data-assisted modeling for advanced material applications.
Area of Science:
- Materials Science
- Condensed Matter Physics
- Computational Chemistry
Background:
- Two-dimensional (2D) materials and their bilayers are pivotal for next-generation electronics.
- Diverse applications span optoelectronics, thermoelectrics, and topological science.
- Understanding interlayer interactions is key to harnessing bilayer properties.
Purpose of the Study:
- To create a comprehensive computational dataset of bilayer materials.
- To characterize structural, electronic, and transport properties of various stacking configurations.
- To facilitate materials screening and data-driven design for specific applications.
Main Methods:
- Analysis of monolayer symmetries to define bilayer stacking patterns.
- Density functional theory (DFT) calculations with van der Waals interactions.
- Evaluation of binding energies and interlayer charge transfer for coupling strength.
Main Results:
- A dataset of 760 bilayer structures with computed properties.
- Accurate identification of ground states for known materials like transition metal dichalcogenides, graphene, boron nitride, and silicene.
- Quantification of interlayer coupling through binding energies and charge transfer.
Conclusions:
- The developed dataset provides a valuable resource for materials discovery.
- Enables efficient screening for materials with desired thermoelectric or optoelectronic properties.
- Supports data-assisted modeling approaches in materials science.
